Presentation on theme: "Raster lidar data visualizations for interpretation of microrelief structures dr. Žiga Kokalj ZRC SAZU Centre of Excellence for Space Sciences and Technologies."— Presentation transcript:
1 Raster lidar data visualizations for interpretation of microrelief structures dr. Žiga KokaljZRC SAZUCentre of Excellence for Space Sciences and Technologies – Space-Si
3 Lidar and past cultural landscapes forest cover in Europe is growingSlovenia: 39% --> 60% in the last centuryDEM’s and DSM’s are mainly provided by lidar operators or national mapping authoritiesthey are not optimised for archaeological detection or interpretationDTM – DSMadvanced visualisation is rarely used
4 Visualizations simplify interpretation of features there is more to visualizations than shaded reliefinterpretation based solely on shaded relief has a big potential to miss important archaeological features (Challis et al Antiquity)
5 Visualizations 1 Analytical hill-shading 2 PCA of hill-shadings 3 Colour cast4 Trend removal5 Slope gradient6 Sky view factor7 Openess8 Solar insolationKokalj et al Antiquity.Kokalj et al Visualizations of lidar derived relief models.
6 Tonovcov gradone of the largest and most important Late Antiquity settlements in the south-eastern Alps3 early Christian churches from the 5th centuryFoto: Željko Cimprič
9 Lidar survey Scanning Data processing scanner type Riegl LMS-Q560 platformhelicopterdate4th and 16th March 2007swath width60 mflying height450 maverage last and only returns per m2 on a combined dataset11.2Data processingmethodREIN (Kobler et al. 2007)spatial resolution of the final elevation model0.5 m
10 1Hill-shadingthe most commonly used technique (Yoëli Kartographische Nachrichten)greyscale colour table – enhances the perception of morphologystandard: azimuth at 315°, sun elevation at 45°surface is illuminated by a direct lightconstant for the entire dataset
11 Shaded relief 315° 45° 50 m Lidar Data Copyright Walks of Peace in the Soča Region Foundation50 m315° °
12 Hill-shading easy to compute and interpret included in standard GIS softwarereveals features with low light source on flat areasdark shades and brightly lit areaslinear structures parallel to the light source
13 Low light shading 315° 45° 5° 50 m Lidar Data Copyright Discovery Programme50 m315°45°5°
30 Slope gradient easy to compute and interpret included in standard GIS softwareworks well in combination with hill-shadingworks well on most types of terrainretains saturated areasadditional information needed for interpretation
31 6 Sky View Factor determines the size of the visible sky elevation angle is determined into multiple directions and to the given distanceconsiders a hemisphere onlyvalues between 0 and 1Kokalj et al Antiquity.
35 SVF – Noisy data 16 10 m (10 px) 100 m Lidar Data Copyright State Office for Cultural Heritage Baden-Wurttemberg100 mm (10 px)
36 Anisotropic SVF 1 0.8 16 10 m (20 px) 100 m Lidar Data Copyright Janus Pannonius Archaeology Museu100 mm (20 px)
37 Sky View Factor no saturations clear distinction between protruding features and depressionsparticularly useful for complex featureshelps with noisy dataintuitive“washout effect” on very flat terrain with very low protruding features
38 7 Openness quantifies the degree of unobstructedness of a location very similar to SVFpositive and negativeDoneus Remote Sensing.
43 Openness no saturations enhances concavities and convexities useful for complex featurescompletely removes general topographyuseful for automatic detectionthe same value on different slopesnegative openness not very intuitive to interpret
44 8 Solar insolation amount of the solar energy received at the surface direct, diffuse and global solar insolationChallis et al Archaeological Prospection.
47 Solar insolation preserves a sense of general topography suitability of land for human activitiescomplex and time consuming calculationsnumerous options can confuse the user“washout effect” on very flat terrain
54 Visualizations for scientific publications because several factor have a big influence on how features are displayed it is imperative to include at least the following into the description of an image:visualization methodcolour legenddata rangedata stretch type
55 Some help http:\\iaps.zrc-sazu.si/en/svf Relief Visualization Toolbox standalone and IDL codeArcGIS toolboxhill-shading in 16 directions,PCA,minimum, maximum and a range of values for hill-shadings,slope severity,simplified version of a solar insolation calculation toolsimplified version of trend removal.Lidar Visualisation Toolbox – standalone
56 ReferencesKokalj, Ž., Oštir, K., Zakšek, K Application of sky-view factor for the visualization of historic landscape features in lidar-derived relief models. Antiquity 85, 327:Kokalj, Ž., Zakšek, K., Oštir, K Visualizations of lidar derived relief models. In: Opitz, R., Cowley., D. (eds) Interpreting archaeological topography – airborne laser scanning, aerial photographs and ground observation. PpŠtular, B., Kokalj, Ž., Oštir, K., Nuniger, L Visualization of lidar-derived relief models for detection of archaeological features. Journal of Archaeological Science 39:Yoëli, P Analytische Schattierung. Ein kartographischer Entwurf. Kartographische Nachrichten 15:Devereux, B.J., Amable, G.S., Crow, P Visualisation of LiDAR terrain models for archaeological feature detection. Antiquity 82, 316:Challis, K Airborne laser altimetry in alluviated landscapes. Archaeological Prospection 13, 2:Challis, K., Kokalj, Ž., Kincey, M., Moscrop, D., Howard, A.J Airborne lidar and historic environment records. Antiquity 82, 318:Hesse R LiDAR-derived Local Relief Models - a new tool for archaeological prospection. Archaeological Prospection 17, 2:Doneus, M., Briese, Ch Full-waveform airborne laser scanning as a tool for archaeological reconnaissance. In: "From Space To Place. Proceedings of The 2nd International Conference On Remote Sensing In Archaeology", Bar International Series, 1568 (2006), , December 2006.Doneus, M Openness as visualization technique for interpretative mapping of airborne LiDAR derived digital terrain models. Remote Sensing 5:
57 Thank you for your attention. ziga. kokalj@zrc-sazu. si http:\\iaps